Overview

Brought to you by YData

Dataset statistics

Number of variables30
Number of observations10000
Missing cells117476
Missing cells (%)39.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory379.5 B

Variable types

Categorical3
DateTime1
Numeric24
Unsupported2

Alerts

total_cases is highly overall correlated with continent and 16 other fieldsHigh correlation
new_cases is highly overall correlated with continent and 18 other fieldsHigh correlation
new_cases_smoothed is highly overall correlated with continent and 18 other fieldsHigh correlation
total_deaths is highly overall correlated with new_cases and 8 other fieldsHigh correlation
new_deaths is highly overall correlated with hosp_patients and 12 other fieldsHigh correlation
new_deaths_smoothed is highly overall correlated with hosp_patients and 12 other fieldsHigh correlation
total_cases_per_million is highly overall correlated with hosp_patients and 12 other fieldsHigh correlation
new_cases_per_million is highly overall correlated with hosp_patients and 13 other fieldsHigh correlation
new_cases_smoothed_per_million is highly overall correlated with hosp_patients and 12 other fieldsHigh correlation
total_deaths_per_million is highly overall correlated with hosp_patients and 6 other fieldsHigh correlation
new_deaths_per_million is highly overall correlated with hosp_patients and 15 other fieldsHigh correlation
new_deaths_smoothed_per_million is highly overall correlated with hosp_patients and 15 other fieldsHigh correlation
icu_patients is highly overall correlated with continent and 17 other fieldsHigh correlation
icu_patients_per_million is highly overall correlated with continent and 17 other fieldsHigh correlation
hosp_patients is highly overall correlated with continent and 16 other fieldsHigh correlation
hosp_patients_per_million is highly overall correlated with continent and 15 other fieldsHigh correlation
weekly_hosp_admissions is highly overall correlated with continent and 15 other fieldsHigh correlation
weekly_hosp_admissions_per_million is highly overall correlated with continent and 15 other fieldsHigh correlation
new_tests is highly overall correlated with icu_patients_per_million and 8 other fieldsHigh correlation
total_tests is highly overall correlated with new_cases and 8 other fieldsHigh correlation
total_tests_per_thousand is highly overall correlated with new_tests and 5 other fieldsHigh correlation
new_tests_per_thousand is highly overall correlated with new_tests and 4 other fieldsHigh correlation
new_tests_smoothed is highly overall correlated with icu_patients and 9 other fieldsHigh correlation
iso_code is highly overall correlated with continent and 3 other fieldsHigh correlation
continent is highly overall correlated with hosp_patients and 10 other fieldsHigh correlation
location is highly overall correlated with continent and 3 other fieldsHigh correlation
continent has 908 (9.1%) missing values Missing
total_cases has 299 (3.0%) missing values Missing
new_cases has 298 (3.0%) missing values Missing
new_cases_smoothed has 415 (4.2%) missing values Missing
total_deaths has 1009 (10.1%) missing values Missing
new_deaths has 985 (9.8%) missing values Missing
new_deaths_smoothed has 415 (4.2%) missing values Missing
total_cases_per_million has 299 (3.0%) missing values Missing
new_cases_per_million has 298 (3.0%) missing values Missing
new_cases_smoothed_per_million has 415 (4.2%) missing values Missing
total_deaths_per_million has 1009 (10.1%) missing values Missing
new_deaths_per_million has 985 (9.8%) missing values Missing
new_deaths_smoothed_per_million has 415 (4.2%) missing values Missing
reproduction_rate has 2379 (23.8%) missing values Missing
icu_patients has 9203 (92.0%) missing values Missing
icu_patients_per_million has 9203 (92.0%) missing values Missing
hosp_patients has 9203 (92.0%) missing values Missing
hosp_patients_per_million has 9203 (92.0%) missing values Missing
weekly_icu_admissions has 10000 (100.0%) missing values Missing
weekly_icu_admissions_per_million has 10000 (100.0%) missing values Missing
weekly_hosp_admissions has 9941 (99.4%) missing values Missing
weekly_hosp_admissions_per_million has 9941 (99.4%) missing values Missing
new_tests has 6453 (64.5%) missing values Missing
total_tests has 6154 (61.5%) missing values Missing
total_tests_per_thousand has 6154 (61.5%) missing values Missing
new_tests_per_thousand has 6453 (64.5%) missing values Missing
new_tests_smoothed has 5439 (54.4%) missing values Missing
new_tests is highly skewed (γ1 = 25.7194316) Skewed
new_tests_per_thousand is highly skewed (γ1 = 24.75830362) Skewed
weekly_icu_admissions is an unsupported type, check if it needs cleaning or further analysis Unsupported
weekly_icu_admissions_per_million is an unsupported type, check if it needs cleaning or further analysis Unsupported
new_cases has 1646 (16.5%) zeros Zeros
new_cases_smoothed has 286 (2.9%) zeros Zeros
new_deaths has 3012 (30.1%) zeros Zeros
new_deaths_smoothed has 2218 (22.2%) zeros Zeros
new_cases_per_million has 1646 (16.5%) zeros Zeros
new_cases_smoothed_per_million has 294 (2.9%) zeros Zeros
new_deaths_per_million has 3014 (30.1%) zeros Zeros
new_deaths_smoothed_per_million has 2223 (22.2%) zeros Zeros

Reproduction

Analysis started2025-02-08 10:47:56.659378
Analysis finished2025-02-08 10:48:32.815440
Duration36.16 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

iso_code
Categorical

High correlation 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size512.4 KiB
ARG
 
486
OWID_ASI
 
465
AUS
 
461
BEL
 
452
OWID_AFR
 
443
Other values (21)
7693 

Length

Max length8
Median length3
Mean length3.454
Min length3

Characters and Unicode

Total characters34540
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAFG
2nd rowAFG
3rd rowAFG
4th rowAFG
5th rowAFG

Common Values

ValueCountFrequency (%)
ARG 486
 
4.9%
OWID_ASI 465
 
4.7%
AUS 461
 
4.6%
BEL 452
 
4.5%
OWID_AFR 443
 
4.4%
AFG 432
 
4.3%
BHR 432
 
4.3%
ALB 431
 
4.3%
DZA 431
 
4.3%
AUT 431
 
4.3%
Other values (16) 5536
55.4%

Length

2025-02-08T16:18:32.850434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
arg 486
 
4.9%
owid_asi 465
 
4.7%
aus 461
 
4.6%
bel 452
 
4.5%
owid_afr 443
 
4.4%
afg 432
 
4.3%
bhr 432
 
4.3%
alb 431
 
4.3%
dza 431
 
4.3%
aut 431
 
4.3%
Other values (16) 5536
55.4%

Most occurring characters

ValueCountFrequency (%)
A 5867
17.0%
B 5085
14.7%
R 2625
 
7.6%
D 2188
 
6.3%
G 2163
 
6.3%
L 2026
 
5.9%
O 1626
 
4.7%
I 1451
 
4.2%
S 1337
 
3.9%
E 1289
 
3.7%
Other values (9) 8883
25.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34540
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 5867
17.0%
B 5085
14.7%
R 2625
 
7.6%
D 2188
 
6.3%
G 2163
 
6.3%
L 2026
 
5.9%
O 1626
 
4.7%
I 1451
 
4.2%
S 1337
 
3.9%
E 1289
 
3.7%
Other values (9) 8883
25.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34540
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 5867
17.0%
B 5085
14.7%
R 2625
 
7.6%
D 2188
 
6.3%
G 2163
 
6.3%
L 2026
 
5.9%
O 1626
 
4.7%
I 1451
 
4.2%
S 1337
 
3.9%
E 1289
 
3.7%
Other values (9) 8883
25.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34540
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 5867
17.0%
B 5085
14.7%
R 2625
 
7.6%
D 2188
 
6.3%
G 2163
 
6.3%
L 2026
 
5.9%
O 1626
 
4.7%
I 1451
 
4.2%
S 1337
 
3.9%
E 1289
 
3.7%
Other values (9) 8883
25.7%

continent
Categorical

High correlation  Missing 

Distinct6
Distinct (%)0.1%
Missing908
Missing (%)9.1%
Memory size551.7 KiB
Asia
2561 
Europe
2167 
North America
1857 
Africa
1249 
South America
797 

Length

Max length13
Median length7
Mean length7.5306863
Min length4

Characters and Unicode

Total characters68469
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAsia
2nd rowAsia
3rd rowAsia
4th rowAsia
5th rowAsia

Common Values

ValueCountFrequency (%)
Asia 2561
25.6%
Europe 2167
21.7%
North America 1857
18.6%
Africa 1249
12.5%
South America 797
 
8.0%
Oceania 461
 
4.6%
(Missing) 908
 
9.1%

Length

2025-02-08T16:18:32.899434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-08T16:18:32.942432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
america 2654
22.6%
asia 2561
21.8%
europe 2167
18.4%
north 1857
15.8%
africa 1249
10.6%
south 797
 
6.8%
oceania 461
 
3.9%

Most occurring characters

ValueCountFrequency (%)
r 7927
11.6%
a 7386
10.8%
i 6925
10.1%
A 6464
 
9.4%
e 5282
 
7.7%
o 4821
 
7.0%
c 4364
 
6.4%
u 2964
 
4.3%
m 2654
 
3.9%
t 2654
 
3.9%
Other values (10) 17028
24.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 68469
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 7927
11.6%
a 7386
10.8%
i 6925
10.1%
A 6464
 
9.4%
e 5282
 
7.7%
o 4821
 
7.0%
c 4364
 
6.4%
u 2964
 
4.3%
m 2654
 
3.9%
t 2654
 
3.9%
Other values (10) 17028
24.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 68469
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 7927
11.6%
a 7386
10.8%
i 6925
10.1%
A 6464
 
9.4%
e 5282
 
7.7%
o 4821
 
7.0%
c 4364
 
6.4%
u 2964
 
4.3%
m 2654
 
3.9%
t 2654
 
3.9%
Other values (10) 17028
24.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 68469
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 7927
11.6%
a 7386
10.8%
i 6925
10.1%
A 6464
 
9.4%
e 5282
 
7.7%
o 4821
 
7.0%
c 4364
 
6.4%
u 2964
 
4.3%
m 2654
 
3.9%
t 2654
 
3.9%
Other values (10) 17028
24.9%

location
Categorical

High correlation 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size554.5 KiB
Argentina
 
486
Asia
 
465
Australia
 
461
Belgium
 
452
Africa
 
443
Other values (21)
7693 

Length

Max length19
Median length11
Mean length7.767
Min length4

Characters and Unicode

Total characters77670
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAfghanistan
2nd rowAfghanistan
3rd rowAfghanistan
4th rowAfghanistan
5th rowAfghanistan

Common Values

ValueCountFrequency (%)
Argentina 486
 
4.9%
Asia 465
 
4.7%
Australia 461
 
4.6%
Belgium 452
 
4.5%
Africa 443
 
4.4%
Afghanistan 432
 
4.3%
Bahrain 432
 
4.3%
Albania 431
 
4.3%
Algeria 431
 
4.3%
Austria 431
 
4.3%
Other values (16) 5536
55.4%

Length

2025-02-08T16:18:33.008435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
argentina 486
 
4.5%
asia 465
 
4.3%
australia 461
 
4.3%
belgium 452
 
4.2%
africa 443
 
4.1%
afghanistan 432
 
4.0%
bahrain 432
 
4.0%
albania 431
 
4.0%
algeria 431
 
4.0%
austria 431
 
4.0%
Other values (18) 6364
58.8%

Most occurring characters

ValueCountFrequency (%)
a 13813
17.8%
i 7245
 
9.3%
n 6956
 
9.0%
A 5789
 
7.5%
r 5778
 
7.4%
B 4625
 
6.0%
e 4399
 
5.7%
l 3905
 
5.0%
s 3462
 
4.5%
u 3239
 
4.2%
Other values (13) 18459
23.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 77670
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 13813
17.8%
i 7245
 
9.3%
n 6956
 
9.0%
A 5789
 
7.5%
r 5778
 
7.4%
B 4625
 
6.0%
e 4399
 
5.7%
l 3905
 
5.0%
s 3462
 
4.5%
u 3239
 
4.2%
Other values (13) 18459
23.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 77670
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 13813
17.8%
i 7245
 
9.3%
n 6956
 
9.0%
A 5789
 
7.5%
r 5778
 
7.4%
B 4625
 
6.0%
e 4399
 
5.7%
l 3905
 
5.0%
s 3462
 
4.5%
u 3239
 
4.2%
Other values (13) 18459
23.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 77670
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 13813
17.8%
i 7245
 
9.3%
n 6956
 
9.0%
A 5789
 
7.5%
r 5778
 
7.4%
B 4625
 
6.0%
e 4399
 
5.7%
l 3905
 
5.0%
s 3462
 
4.5%
u 3239
 
4.2%
Other values (13) 18459
23.8%

date
Date

Distinct486
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
Minimum2020-01-01 00:00:00
Maximum2021-04-30 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-08T16:18:33.068432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:33.136433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

total_cases
Real number (ℝ)

High correlation  Missing 

Distinct7269
Distinct (%)74.9%
Missing299
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean725597.78
Minimum1
Maximum39526308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:33.200434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q11036
median19883
Q3123345
95-th percentile2278115
Maximum39526308
Range39526307
Interquartile range (IQR)122309

Descriptive statistics

Standard deviation3395909.8
Coefficient of variation (CV)4.6801546
Kurtosis51.522104
Mean725597.78
Median Absolute Deviation (MAD)19808
Skewness6.9032953
Sum7.0390241 × 109
Variance1.1532203 × 1013
MonotonicityNot monotonic
2025-02-08T16:18:33.266432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 117
 
1.2%
18 59
 
0.6%
92 40
 
0.4%
25 37
 
0.4%
2 33
 
0.3%
26 33
 
0.3%
5 31
 
0.3%
7 31
 
0.3%
3 31
 
0.3%
15 31
 
0.3%
Other values (7259) 9258
92.6%
(Missing) 299
 
3.0%
ValueCountFrequency (%)
1 117
1.2%
2 33
 
0.3%
3 31
 
0.3%
4 18
 
0.2%
5 31
 
0.3%
6 19
 
0.2%
7 31
 
0.3%
8 10
 
0.1%
9 13
 
0.1%
10 8
 
0.1%
ValueCountFrequency (%)
39526308 1
< 0.1%
39007933 1
< 0.1%
38492711 1
< 0.1%
37986034 1
< 0.1%
37496027 1
< 0.1%
37055035 1
< 0.1%
36576350 1
< 0.1%
36102612 1
< 0.1%
35621281 1
< 0.1%
35138536 1
< 0.1%

new_cases
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct2913
Distinct (%)30.0%
Missing298
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean5182.4356
Minimum-209
Maximum518375
Zeros1646
Zeros (%)16.5%
Negative2
Negative (%)< 0.1%
Memory size78.3 KiB
2025-02-08T16:18:33.333433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-209
5-th percentile0
Q16
median125
Q3920.75
95-th percentile15452.4
Maximum518375
Range518584
Interquartile range (IQR)914.75

Descriptive statistics

Standard deviation26489.794
Coefficient of variation (CV)5.1114566
Kurtosis164.88754
Mean5182.4356
Median Absolute Deviation (MAD)125
Skewness11.142347
Sum50279990
Variance7.0170921 × 108
MonotonicityNot monotonic
2025-02-08T16:18:33.396432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1646
 
16.5%
1 278
 
2.8%
2 143
 
1.4%
3 120
 
1.2%
4 103
 
1.0%
6 78
 
0.8%
5 78
 
0.8%
8 70
 
0.7%
7 69
 
0.7%
11 61
 
0.6%
Other values (2903) 7056
70.6%
(Missing) 298
 
3.0%
ValueCountFrequency (%)
-209 1
 
< 0.1%
-1 1
 
< 0.1%
0 1646
16.5%
1 278
 
2.8%
2 143
 
1.4%
3 120
 
1.2%
4 103
 
1.0%
5 78
 
0.8%
6 78
 
0.8%
7 69
 
0.7%
ValueCountFrequency (%)
518375 1
< 0.1%
515222 1
< 0.1%
506677 1
< 0.1%
490007 1
< 0.1%
482745 1
< 0.1%
481331 1
< 0.1%
478685 1
< 0.1%
473738 1
< 0.1%
471579 1
< 0.1%
448580 1
< 0.1%

new_cases_smoothed
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct4921
Distinct (%)51.3%
Missing415
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean5073.0601
Minimum-29.143
Maximum489099.43
Zeros286
Zeros (%)2.9%
Negative8
Negative (%)0.1%
Memory size78.3 KiB
2025-02-08T16:18:33.459432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-29.143
5-th percentile0.286
Q112.143
median125.571
Q3938.857
95-th percentile14739.115
Maximum489099.43
Range489128.57
Interquartile range (IQR)926.714

Descriptive statistics

Standard deviation25064.839
Coefficient of variation (CV)4.9407731
Kurtosis155.82431
Mean5073.0601
Median Absolute Deviation (MAD)124.857
Skewness10.70028
Sum48625281
Variance6.2824613 × 108
MonotonicityNot monotonic
2025-02-08T16:18:33.524432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 286
 
2.9%
0.143 180
 
1.8%
0.286 134
 
1.3%
0.571 106
 
1.1%
0.429 98
 
1.0%
0.714 97
 
1.0%
0.857 76
 
0.8%
1.286 66
 
0.7%
1.143 63
 
0.6%
1 60
 
0.6%
Other values (4911) 8419
84.2%
(Missing) 415
 
4.2%
ValueCountFrequency (%)
-29.143 3
 
< 0.1%
-28.143 2
 
< 0.1%
-21.143 2
 
< 0.1%
-0.143 1
 
< 0.1%
0 286
2.9%
0.143 180
1.8%
0.286 134
1.3%
0.429 98
 
1.0%
0.571 106
 
1.1%
0.714 97
 
1.0%
ValueCountFrequency (%)
489099.429 1
< 0.1%
483807.429 1
< 0.1%
479167.857 1
< 0.1%
474153.857 1
< 0.1%
468235.714 1
< 0.1%
462347.286 1
< 0.1%
453217 1
< 0.1%
444080.429 1
< 0.1%
430847.714 1
< 0.1%
414971 1
< 0.1%

total_deaths
Real number (ℝ)

High correlation  Missing 

Distinct3946
Distinct (%)43.9%
Missing1009
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean14507.746
Minimum1
Maximum520286
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:33.588433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q146
median524
Q33073
95-th percentile58941
Maximum520286
Range520285
Interquartile range (IQR)3027

Descriptive statistics

Standard deviation56315.495
Coefficient of variation (CV)3.8817537
Kurtosis35.562896
Mean14507.746
Median Absolute Deviation (MAD)517
Skewness5.7843188
Sum1.3043914 × 108
Variance3.171435 × 109
MonotonicityNot monotonic
2025-02-08T16:18:33.652434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 300
 
3.0%
3 271
 
2.7%
2 230
 
2.3%
1 202
 
2.0%
11 113
 
1.1%
909 107
 
1.1%
4 99
 
1.0%
44 73
 
0.7%
52 66
 
0.7%
5 66
 
0.7%
Other values (3936) 7464
74.6%
(Missing) 1009
 
10.1%
ValueCountFrequency (%)
1 202
2.0%
2 230
2.3%
3 271
2.7%
4 99
 
1.0%
5 66
 
0.7%
6 47
 
0.5%
7 300
3.0%
8 46
 
0.5%
9 30
 
0.3%
10 23
 
0.2%
ValueCountFrequency (%)
520286 1
< 0.1%
515111 1
< 0.1%
509870 1
< 0.1%
504552 1
< 0.1%
499552 1
< 0.1%
495069 1
< 0.1%
490544 1
< 0.1%
486138 1
< 0.1%
482017 1
< 0.1%
478068 1
< 0.1%

new_deaths
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct761
Distinct (%)8.4%
Missing985
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean86.942651
Minimum-117
Maximum5318
Zeros3012
Zeros (%)30.1%
Negative6
Negative (%)0.1%
Memory size78.3 KiB
2025-02-08T16:18:33.718432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-117
5-th percentile0
Q10
median3
Q319
95-th percentile404.3
Maximum5318
Range5435
Interquartile range (IQR)19

Descriptive statistics

Standard deviation319.4736
Coefficient of variation (CV)3.6745325
Kurtosis65.214933
Mean86.942651
Median Absolute Deviation (MAD)3
Skewness6.7523939
Sum783788
Variance102063.38
MonotonicityNot monotonic
2025-02-08T16:18:33.918839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3012
30.1%
1 710
 
7.1%
2 488
 
4.9%
3 393
 
3.9%
4 353
 
3.5%
5 311
 
3.1%
6 224
 
2.2%
9 190
 
1.9%
7 186
 
1.9%
10 163
 
1.6%
Other values (751) 2985
29.8%
(Missing) 985
 
9.8%
ValueCountFrequency (%)
-117 1
 
< 0.1%
-3 1
 
< 0.1%
-1 4
 
< 0.1%
0 3012
30.1%
1 710
 
7.1%
2 488
 
4.9%
3 393
 
3.9%
4 353
 
3.5%
5 311
 
3.1%
6 224
 
2.2%
ValueCountFrequency (%)
5318 1
< 0.1%
5241 1
< 0.1%
5175 1
< 0.1%
5000 1
< 0.1%
4525 1
< 0.1%
4483 1
< 0.1%
4406 1
< 0.1%
4121 1
< 0.1%
3949 1
< 0.1%
3808 1
< 0.1%

new_deaths_smoothed
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct1532
Distinct (%)16.0%
Missing415
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean79.855738
Minimum-14.429
Maximum4878.286
Zeros2218
Zeros (%)22.2%
Negative14
Negative (%)0.1%
Memory size78.3 KiB
2025-02-08T16:18:33.980845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-14.429
5-th percentile0
Q10.143
median2.571
Q316.429
95-th percentile362.857
Maximum4878.286
Range4892.715
Interquartile range (IQR)16.286

Descriptive statistics

Standard deviation293.05612
Coefficient of variation (CV)3.6698191
Kurtosis55.709251
Mean79.855738
Median Absolute Deviation (MAD)2.571
Skewness6.3310257
Sum765417.25
Variance85881.887
MonotonicityNot monotonic
2025-02-08T16:18:34.043845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2218
22.2%
0.143 507
 
5.1%
0.286 334
 
3.3%
0.429 202
 
2.0%
0.571 174
 
1.7%
0.714 170
 
1.7%
1 141
 
1.4%
0.857 139
 
1.4%
1.143 114
 
1.1%
1.429 107
 
1.1%
Other values (1522) 5479
54.8%
(Missing) 415
 
4.2%
ValueCountFrequency (%)
-14.429 1
 
< 0.1%
-14.143 2
 
< 0.1%
-14 1
 
< 0.1%
-13.857 1
 
< 0.1%
-13.143 1
 
< 0.1%
-12.857 1
 
< 0.1%
-0.143 7
 
0.1%
0 2218
22.2%
0.143 507
 
5.1%
0.286 334
 
3.3%
ValueCountFrequency (%)
4878.286 1
< 0.1%
4727.714 1
< 0.1%
4543.143 1
< 0.1%
4327.429 1
< 0.1%
4143.143 1
< 0.1%
3978.857 1
< 0.1%
3786.286 1
< 0.1%
3575.286 1
< 0.1%
3384.571 1
< 0.1%
3205.286 1
< 0.1%

total_cases_per_million
Real number (ℝ)

High correlation  Missing 

Distinct8036
Distinct (%)82.8%
Missing299
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean12285.905
Minimum0.001
Maximum171254.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:34.104846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile4.454
Q1318.813
median1752.729
Q312348.723
95-th percentile58879.019
Maximum171254.77
Range171254.77
Interquartile range (IQR)12029.91

Descriptive statistics

Standard deviation23360.288
Coefficient of variation (CV)1.9013893
Kurtosis12.443899
Mean12285.905
Median Absolute Deviation (MAD)1716.248
Skewness3.1587086
Sum1.1918556 × 108
Variance5.4570305 × 108
MonotonicityNot monotonic
2025-02-08T16:18:34.169845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45.269 53
 
0.5%
255.29 30
 
0.3%
0.086 26
 
0.3%
11065.812 25
 
0.2%
265.501 25
 
0.2%
0.588 23
 
0.2%
264.464 22
 
0.2%
337.543 20
 
0.2%
6.48 19
 
0.2%
320.144 18
 
0.2%
Other values (8026) 9440
94.4%
(Missing) 299
 
3.0%
ValueCountFrequency (%)
0.001 14
0.1%
0.002 2
 
< 0.1%
0.003 1
 
< 0.1%
0.006 1
 
< 0.1%
0.008 1
 
< 0.1%
0.016 1
 
< 0.1%
0.018 8
0.1%
0.022 3
 
< 0.1%
0.023 6
0.1%
0.026 8
0.1%
ValueCountFrequency (%)
171254.773 1
< 0.1%
170814.729 1
< 0.1%
170167.605 1
< 0.1%
169818.158 1
< 0.1%
169326.344 1
< 0.1%
169028.668 1
< 0.1%
168562.739 1
< 0.1%
168342.717 1
< 0.1%
167501.456 1
< 0.1%
167177.894 1
< 0.1%

new_cases_per_million
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct5491
Distinct (%)56.6%
Missing298
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean83.284129
Minimum-17.24
Maximum3869.799
Zeros1646
Zeros (%)16.5%
Negative2
Negative (%)< 0.1%
Memory size78.3 KiB
2025-02-08T16:18:34.233845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-17.24
5-th percentile0
Q10.974
median10.439
Q390.08
95-th percentile385.523
Maximum3869.799
Range3887.039
Interquartile range (IQR)89.106

Descriptive statistics

Standard deviation190.76866
Coefficient of variation (CV)2.2905765
Kurtosis85.727422
Mean83.284129
Median Absolute Deviation (MAD)10.439
Skewness6.9337918
Sum808022.62
Variance36392.683
MonotonicityNot monotonic
2025-02-08T16:18:34.299845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1646
 
16.5%
3.48 65
 
0.7%
1.296 63
 
0.6%
10.212 34
 
0.3%
2.592 34
 
0.3%
6.96 30
 
0.3%
3.888 24
 
0.2%
2.543 23
 
0.2%
0.235 22
 
0.2%
2.515 22
 
0.2%
Other values (5481) 7739
77.4%
(Missing) 298
 
3.0%
ValueCountFrequency (%)
-17.24 1
 
< 0.1%
-10.212 1
 
< 0.1%
0 1646
16.5%
0.001 4
 
< 0.1%
0.002 2
 
< 0.1%
0.003 1
 
< 0.1%
0.006 2
 
< 0.1%
0.007 1
 
< 0.1%
0.01 2
 
< 0.1%
0.012 6
 
0.1%
ValueCountFrequency (%)
3869.799 1
< 0.1%
3714.489 1
< 0.1%
3475.672 1
< 0.1%
3365.042 1
< 0.1%
3183.848 1
< 0.1%
2937.941 1
< 0.1%
2562.609 1
< 0.1%
2523.782 1
< 0.1%
2433.184 1
< 0.1%
2420.242 1
< 0.1%

new_cases_smoothed_per_million
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct6796
Distinct (%)70.9%
Missing415
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean83.280987
Minimum-2.404
Maximum1536.03
Zeros294
Zeros (%)2.9%
Negative8
Negative (%)0.1%
Memory size78.3 KiB
2025-02-08T16:18:34.364845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2.404
5-th percentile0.0662
Q12.438
median12.919
Q3101.895
95-th percentile381.2428
Maximum1536.03
Range1538.434
Interquartile range (IQR)99.457

Descriptive statistics

Standard deviation159.48804
Coefficient of variation (CV)1.9150594
Kurtosis17.481932
Mean83.280987
Median Absolute Deviation (MAD)12.422
Skewness3.5879146
Sum798248.26
Variance25436.435
MonotonicityNot monotonic
2025-02-08T16:18:34.428846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 294
 
2.9%
1.459 58
 
0.6%
0.185 40
 
0.4%
2.486 33
 
0.3%
5.835 33
 
0.3%
2.918 32
 
0.3%
0.719 30
 
0.3%
0.37 28
 
0.3%
1.988 28
 
0.3%
0.555 25
 
0.2%
Other values (6786) 8984
89.8%
(Missing) 415
 
4.2%
ValueCountFrequency (%)
-2.404 3
 
< 0.1%
-2.321 2
 
< 0.1%
-1.744 2
 
< 0.1%
-1.459 1
 
< 0.1%
0 294
2.9%
0.001 2
 
< 0.1%
0.002 3
 
< 0.1%
0.003 3
 
< 0.1%
0.004 7
 
0.1%
0.006 2
 
< 0.1%
ValueCountFrequency (%)
1536.03 1
< 0.1%
1526.243 1
< 0.1%
1505.362 1
< 0.1%
1478.996 1
< 0.1%
1455.103 2
< 0.1%
1416.921 1
< 0.1%
1400.724 1
< 0.1%
1397.787 1
< 0.1%
1327.528 1
< 0.1%
1320.517 1
< 0.1%

total_deaths_per_million
Real number (ℝ)

High correlation  Missing 

Distinct5896
Distinct (%)65.6%
Missing1009
Missing (%)10.1%
Infinite0
Infinite (%)0.0%
Mean243.36239
Minimum0.001
Maximum2090.665
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:34.492846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile0.684
Q113.9425
median50.902
Q3289.6395
95-th percentile1087.168
Maximum2090.665
Range2090.664
Interquartile range (IQR)275.697

Descriptive statistics

Standard deviation394.14365
Coefficient of variation (CV)1.619575
Kurtosis4.4081792
Mean243.36239
Median Absolute Deviation (MAD)46.957
Skewness2.1372468
Sum2188071.3
Variance155349.22
MonotonicityNot monotonic
2025-02-08T16:18:34.552845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.359 266
 
2.7%
30.635 212
 
2.1%
5.03 127
 
1.3%
1.296 113
 
1.1%
35.647 106
 
1.1%
27.972 98
 
1.0%
673.008 57
 
0.6%
685.951 57
 
0.6%
0.061 50
 
0.5%
3.629 40
 
0.4%
Other values (5886) 7865
78.6%
(Missing) 1009
 
10.1%
ValueCountFrequency (%)
0.001 4
< 0.1%
0.002 1
 
< 0.1%
0.004 3
< 0.1%
0.005 1
 
< 0.1%
0.006 6
0.1%
0.008 1
 
< 0.1%
0.009 1
 
< 0.1%
0.012 3
< 0.1%
0.013 1
 
< 0.1%
0.015 1
 
< 0.1%
ValueCountFrequency (%)
2090.665 1
< 0.1%
2086.782 1
< 0.1%
2082.899 1
< 0.1%
2079.793 1
< 0.1%
2076.428 1
< 0.1%
2072.89 1
< 0.1%
2069.956 1
< 0.1%
2066.85 1
< 0.1%
2062.967 1
< 0.1%
2059.343 1
< 0.1%

new_deaths_per_million
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct1138
Distinct (%)12.6%
Missing985
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean1.4045902
Minimum-10.095
Maximum141.865
Zeros3014
Zeros (%)30.1%
Negative6
Negative (%)0.1%
Memory size78.3 KiB
2025-02-08T16:18:34.610847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-10.095
5-th percentile0
Q10
median0.177
Q31.035
95-th percentile7.087
Maximum141.865
Range151.96
Interquartile range (IQR)1.035

Descriptive statistics

Standard deviation3.8340917
Coefficient of variation (CV)2.729687
Kurtosis257.45195
Mean1.4045902
Median Absolute Deviation (MAD)0.177
Skewness10.780531
Sum12662.381
Variance14.700259
MonotonicityNot monotonic
2025-02-08T16:18:34.676846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3014
30.1%
0.03 101
 
1.0%
0.588 101
 
1.0%
0.091 96
 
1.0%
0.952 77
 
0.8%
0.061 76
 
0.8%
0.529 71
 
0.7%
1.175 66
 
0.7%
0.197 60
 
0.6%
12.942 59
 
0.6%
Other values (1128) 5294
52.9%
(Missing) 985
 
9.8%
ValueCountFrequency (%)
-10.095 1
 
< 0.1%
-2.515 1
 
< 0.1%
-0.111 2
 
< 0.1%
-0.091 1
 
< 0.1%
-0.039 1
 
< 0.1%
0 3014
30.1%
0.001 7
 
0.1%
0.002 5
 
0.1%
0.003 2
 
< 0.1%
0.004 2
 
< 0.1%
ValueCountFrequency (%)
141.865 1
 
< 0.1%
77.655 1
 
< 0.1%
74.144 1
 
< 0.1%
51.77 1
 
< 0.1%
51.058 1
 
< 0.1%
42.797 1
 
< 0.1%
40.239 1
 
< 0.1%
38.827 8
0.1%
38.144 1
 
< 0.1%
35.98 1
 
< 0.1%

new_deaths_smoothed_per_million
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct1851
Distinct (%)19.3%
Missing415
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean1.3082388
Minimum-1.245
Maximum28.77
Zeros2223
Zeros (%)22.2%
Negative14
Negative (%)0.1%
Memory size78.3 KiB
2025-02-08T16:18:34.739845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1.245
5-th percentile0
Q10.011
median0.212
Q31.277
95-th percentile6.5296
Maximum28.77
Range30.015
Interquartile range (IQR)1.266

Descriptive statistics

Standard deviation2.7243264
Coefficient of variation (CV)2.0824381
Kurtosis22.740144
Mean1.3082388
Median Absolute Deviation (MAD)0.212
Skewness4.0582871
Sum12539.469
Variance7.4219543
MonotonicityNot monotonic
2025-02-08T16:18:34.802839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2223
 
22.2%
1.849 67
 
0.7%
0.363 66
 
0.7%
0.012 64
 
0.6%
1.459 64
 
0.6%
0.024 55
 
0.5%
0.006 53
 
0.5%
0.048 51
 
0.5%
0.035 51
 
0.5%
3.698 51
 
0.5%
Other values (1841) 6840
68.4%
(Missing) 415
 
4.2%
ValueCountFrequency (%)
-1.245 1
 
< 0.1%
-1.22 2
 
< 0.1%
-1.208 1
 
< 0.1%
-1.196 1
 
< 0.1%
-1.134 1
 
< 0.1%
-1.109 1
 
< 0.1%
-0.359 1
 
< 0.1%
-0.006 6
 
0.1%
0 2223
22.2%
0.001 12
 
0.1%
ValueCountFrequency (%)
28.77 1
< 0.1%
27.993 1
< 0.1%
27.118 1
< 0.1%
26.539 1
< 0.1%
26.428 1
< 0.1%
26.156 1
< 0.1%
25.972 1
< 0.1%
25.885 1
< 0.1%
25.676 1
< 0.1%
25.429 1
< 0.1%

reproduction_rate
Real number (ℝ)

Missing 

Distinct245
Distinct (%)3.2%
Missing2379
Missing (%)23.8%
Infinite0
Infinite (%)0.0%
Mean1.0379845
Minimum0.09
Maximum3.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:34.864845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.09
5-th percentile0.59
Q10.86
median1.02
Q31.18
95-th percentile1.52
Maximum3.13
Range3.04
Interquartile range (IQR)0.32

Descriptive statistics

Standard deviation0.30815032
Coefficient of variation (CV)0.29687372
Kurtosis5.2576888
Mean1.0379845
Median Absolute Deviation (MAD)0.16
Skewness1.1048186
Sum7910.48
Variance0.09495662
MonotonicityNot monotonic
2025-02-08T16:18:34.924840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.97 158
 
1.6%
0.94 142
 
1.4%
0.99 142
 
1.4%
0.88 135
 
1.4%
1.13 135
 
1.4%
0.87 131
 
1.3%
1.08 126
 
1.3%
1.11 126
 
1.3%
0.98 126
 
1.3%
1.1 126
 
1.3%
Other values (235) 6274
62.7%
(Missing) 2379
 
23.8%
ValueCountFrequency (%)
0.09 1
 
< 0.1%
0.1 7
0.1%
0.11 2
 
< 0.1%
0.12 1
 
< 0.1%
0.13 2
 
< 0.1%
0.14 2
 
< 0.1%
0.15 1
 
< 0.1%
0.16 4
< 0.1%
0.17 1
 
< 0.1%
0.18 2
 
< 0.1%
ValueCountFrequency (%)
3.13 1
< 0.1%
3.04 1
< 0.1%
3.01 1
< 0.1%
2.99 1
< 0.1%
2.93 1
< 0.1%
2.88 1
< 0.1%
2.87 1
< 0.1%
2.8 1
< 0.1%
2.77 2
< 0.1%
2.74 2
< 0.1%

icu_patients
Real number (ℝ)

High correlation  Missing 

Distinct488
Distinct (%)61.2%
Missing9203
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean360.15809
Minimum6
Maximum1474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:34.985845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile15
Q168
median297
Q3536
95-th percentile1124
Maximum1474
Range1468
Interquartile range (IQR)468

Descriptive statistics

Standard deviation346.01563
Coefficient of variation (CV)0.96073264
Kurtosis1.0401967
Mean360.15809
Median Absolute Deviation (MAD)230
Skewness1.2248871
Sum287046
Variance119726.82
MonotonicityNot monotonic
2025-02-08T16:18:35.048846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11 9
 
0.1%
28 8
 
0.1%
23 8
 
0.1%
10 8
 
0.1%
32 7
 
0.1%
30 7
 
0.1%
8 6
 
0.1%
36 6
 
0.1%
25 6
 
0.1%
27 6
 
0.1%
Other values (478) 726
 
7.3%
(Missing) 9203
92.0%
ValueCountFrequency (%)
6 1
 
< 0.1%
7 3
 
< 0.1%
8 6
0.1%
9 6
0.1%
10 8
0.1%
11 9
0.1%
12 3
 
< 0.1%
14 2
 
< 0.1%
15 4
< 0.1%
16 4
< 0.1%
ValueCountFrequency (%)
1474 1
< 0.1%
1470 2
< 0.1%
1464 1
< 0.1%
1463 1
< 0.1%
1459 1
< 0.1%
1457 1
< 0.1%
1456 1
< 0.1%
1439 1
< 0.1%
1428 1
< 0.1%
1423 1
< 0.1%

icu_patients_per_million
Real number (ℝ)

High correlation  Missing 

Distinct572
Distinct (%)71.8%
Missing9203
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean33.991079
Minimum0.666
Maximum127.183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.112845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.666
5-th percentile1.665
Q16.126
median28.215
Q352.74
95-th percentile96.9834
Maximum127.183
Range126.517
Interquartile range (IQR)46.614

Descriptive statistics

Standard deviation30.813982
Coefficient of variation (CV)0.90653145
Kurtosis0.28415709
Mean33.991079
Median Absolute Deviation (MAD)22.305
Skewness0.96674998
Sum27090.89
Variance949.5015
MonotonicityNot monotonic
2025-02-08T16:18:35.175839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.221 9
 
0.1%
1.11 8
 
0.1%
2.554 7
 
0.1%
0.999 6
 
0.1%
2.776 6
 
0.1%
0.888 6
 
0.1%
1.888 5
 
0.1%
2.443 5
 
0.1%
3.331 5
 
0.1%
2.11 5
 
0.1%
Other values (562) 735
 
7.3%
(Missing) 9203
92.0%
ValueCountFrequency (%)
0.666 1
 
< 0.1%
0.777 3
 
< 0.1%
0.888 6
0.1%
0.999 6
0.1%
1.11 8
0.1%
1.221 9
0.1%
1.332 3
 
< 0.1%
1.554 2
 
< 0.1%
1.665 4
< 0.1%
1.777 4
< 0.1%
ValueCountFrequency (%)
127.183 1
< 0.1%
126.838 2
< 0.1%
126.32 1
< 0.1%
126.234 1
< 0.1%
125.889 1
< 0.1%
125.716 1
< 0.1%
125.63 1
< 0.1%
124.163 1
< 0.1%
123.214 1
< 0.1%
122.782 1
< 0.1%

hosp_patients
Real number (ℝ)

High correlation  Missing 

Distinct670
Distinct (%)84.1%
Missing9203
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean1636.7315
Minimum52
Maximum7461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.236840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum52
5-th percentile69.6
Q1281
median1342
Q32330
95-th percentile5228.8
Maximum7461
Range7409
Interquartile range (IQR)2049

Descriptive statistics

Standard deviation1611.2438
Coefficient of variation (CV)0.98442766
Kurtosis1.6573531
Mean1636.7315
Median Absolute Deviation (MAD)1051
Skewness1.3580877
Sum1304475
Variance2596106.4
MonotonicityNot monotonic
2025-02-08T16:18:35.434845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66 6
 
0.1%
65 6
 
0.1%
62 5
 
0.1%
60 5
 
0.1%
93 4
 
< 0.1%
74 4
 
< 0.1%
92 4
 
< 0.1%
87 3
 
< 0.1%
260 3
 
< 0.1%
96 3
 
< 0.1%
Other values (660) 754
 
7.5%
(Missing) 9203
92.0%
ValueCountFrequency (%)
52 1
 
< 0.1%
55 2
 
< 0.1%
57 2
 
< 0.1%
58 1
 
< 0.1%
59 2
 
< 0.1%
60 5
0.1%
61 2
 
< 0.1%
62 5
0.1%
63 1
 
< 0.1%
64 2
 
< 0.1%
ValueCountFrequency (%)
7461 1
< 0.1%
7411 1
< 0.1%
7290 1
< 0.1%
7233 1
< 0.1%
7224 1
< 0.1%
7221 1
< 0.1%
7058 1
< 0.1%
7010 1
< 0.1%
6955 1
< 0.1%
6895 1
< 0.1%

hosp_patients_per_million
Real number (ℝ)

High correlation  Missing 

Distinct693
Distinct (%)87.0%
Missing9203
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean154.1048
Minimum5.774
Maximum643.766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.496846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.774
5-th percentile7.7276
Q125.454
median139.263
Q3218.989
95-th percentile451.1626
Maximum643.766
Range637.992
Interquartile range (IQR)193.535

Descriptive statistics

Standard deviation144.43984
Coefficient of variation (CV)0.93728317
Kurtosis0.8851217
Mean154.1048
Median Absolute Deviation (MAD)108.2
Skewness1.1483716
Sum122821.53
Variance20862.866
MonotonicityNot monotonic
2025-02-08T16:18:35.558840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.217 6
 
0.1%
7.328 6
 
0.1%
6.662 5
 
0.1%
6.884 5
 
0.1%
10.215 4
 
< 0.1%
8.216 4
 
< 0.1%
10.326 4
 
< 0.1%
9.66 3
 
< 0.1%
7.55 3
 
< 0.1%
9.327 3
 
< 0.1%
Other values (683) 754
 
7.5%
(Missing) 9203
92.0%
ValueCountFrequency (%)
5.774 1
 
< 0.1%
6.107 2
 
< 0.1%
6.329 2
 
< 0.1%
6.44 1
 
< 0.1%
6.551 2
 
< 0.1%
6.662 5
0.1%
6.773 2
 
< 0.1%
6.884 5
0.1%
6.995 1
 
< 0.1%
7.106 2
 
< 0.1%
ValueCountFrequency (%)
643.766 1
< 0.1%
639.452 1
< 0.1%
629.011 1
< 0.1%
624.093 1
< 0.1%
623.317 1
< 0.1%
623.058 1
< 0.1%
608.993 1
< 0.1%
604.852 1
< 0.1%
600.106 1
< 0.1%
594.929 1
< 0.1%

weekly_icu_admissions
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

weekly_icu_admissions_per_million
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

weekly_hosp_admissions
Real number (ℝ)

High correlation  Missing 

Distinct59
Distinct (%)100.0%
Missing9941
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean1179.6511
Minimum70.408
Maximum4759.588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.621846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum70.408
5-th percentile102.3932
Q1242.908
median933.41
Q31630.9535
95-th percentile3526.641
Maximum4759.588
Range4689.18
Interquartile range (IQR)1388.0455

Descriptive statistics

Standard deviation1115.5356
Coefficient of variation (CV)0.9456487
Kurtosis1.832173
Mean1179.6511
Median Absolute Deviation (MAD)704.081
Skewness1.4455839
Sum69599.417
Variance1244419.6
MonotonicityNot monotonic
2025-02-08T16:18:35.682845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.408 1
 
< 0.1%
1507.739 1
 
< 0.1%
3519.399 1
 
< 0.1%
3591.819 1
 
< 0.1%
2846.499 1
 
< 0.1%
1936.223 1
 
< 0.1%
1428.279 1
 
< 0.1%
915.305 1
 
< 0.1%
667.871 1
 
< 0.1%
445.583 1
 
< 0.1%
Other values (49) 49
 
0.5%
(Missing) 9941
99.4%
ValueCountFrequency (%)
70.408 1
< 0.1%
71.414 1
< 0.1%
82.478 1
< 0.1%
104.606 1
< 0.1%
107.624 1
< 0.1%
112.653 1
< 0.1%
130.758 1
< 0.1%
140.816 1
< 0.1%
147.857 1
< 0.1%
153.892 1
< 0.1%
ValueCountFrequency (%)
4759.588 1
< 0.1%
4325.069 1
< 0.1%
3591.819 1
< 0.1%
3519.399 1
< 0.1%
3434.91 1
< 0.1%
3351.426 1
< 0.1%
2846.499 1
< 0.1%
2197.739 1
< 0.1%
1936.223 1
< 0.1%
1859.78 1
< 0.1%

weekly_hosp_admissions_per_million
Real number (ℝ)

High correlation  Missing 

Distinct59
Distinct (%)100.0%
Missing9941
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean101.78515
Minimum6.075
Maximum410.677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.741839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.075
5-th percentile8.8351
Q120.959
median80.538
Q3140.725
95-th percentile304.2929
Maximum410.677
Range404.602
Interquartile range (IQR)119.766

Descriptive statistics

Standard deviation96.253001
Coefficient of variation (CV)0.94564874
Kurtosis1.8321811
Mean101.78515
Median Absolute Deviation (MAD)60.751
Skewness1.4455857
Sum6005.324
Variance9264.6402
MonotonicityNot monotonic
2025-02-08T16:18:35.805847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.075 1
 
< 0.1%
130.094 1
 
< 0.1%
303.668 1
 
< 0.1%
309.917 1
 
< 0.1%
245.608 1
 
< 0.1%
167.065 1
 
< 0.1%
123.238 1
 
< 0.1%
78.976 1
 
< 0.1%
57.627 1
 
< 0.1%
38.447 1
 
< 0.1%
Other values (49) 49
 
0.5%
(Missing) 9941
99.4%
ValueCountFrequency (%)
6.075 1
< 0.1%
6.162 1
< 0.1%
7.117 1
< 0.1%
9.026 1
< 0.1%
9.286 1
< 0.1%
9.72 1
< 0.1%
11.282 1
< 0.1%
12.15 1
< 0.1%
12.758 1
< 0.1%
13.278 1
< 0.1%
ValueCountFrequency (%)
410.677 1
< 0.1%
373.185 1
< 0.1%
309.917 1
< 0.1%
303.668 1
< 0.1%
296.378 1
< 0.1%
289.175 1
< 0.1%
245.608 1
< 0.1%
189.63 1
< 0.1%
167.065 1
< 0.1%
160.469 1
< 0.1%

new_tests
Real number (ℝ)

High correlation  Missing  Skewed 

Distinct3195
Distinct (%)90.1%
Missing6453
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean20929.134
Minimum1
Maximum2945871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.868845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile146.3
Q11870
median8802
Q320782.5
95-th percentile61160
Maximum2945871
Range2945870
Interquartile range (IQR)18912.5

Descriptive statistics

Standard deviation66675.965
Coefficient of variation (CV)3.1857966
Kurtosis1053.6405
Mean20929.134
Median Absolute Deviation (MAD)7542
Skewness25.719432
Sum74235638
Variance4.4456843 × 109
MonotonicityNot monotonic
2025-02-08T16:18:35.932845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 9
 
0.1%
5 8
 
0.1%
2 6
 
0.1%
36 6
 
0.1%
10 5
 
0.1%
35 5
 
0.1%
2714 4
 
< 0.1%
8 4
 
< 0.1%
24 4
 
< 0.1%
7 4
 
< 0.1%
Other values (3185) 3492
34.9%
(Missing) 6453
64.5%
ValueCountFrequency (%)
1 9
0.1%
2 6
0.1%
3 4
< 0.1%
4 3
 
< 0.1%
5 8
0.1%
6 3
 
< 0.1%
7 4
< 0.1%
8 4
< 0.1%
9 2
 
< 0.1%
10 5
0.1%
ValueCountFrequency (%)
2945871 1
< 0.1%
610150 1
< 0.1%
516648 1
< 0.1%
505277 1
< 0.1%
485632 1
< 0.1%
483046 1
< 0.1%
436660 1
< 0.1%
426701 1
< 0.1%
418328 1
< 0.1%
395907 1
< 0.1%

total_tests
Real number (ℝ)

High correlation  Missing 

Distinct3836
Distinct (%)99.7%
Missing6154
Missing (%)61.5%
Infinite0
Infinite (%)0.0%
Mean2461544.9
Minimum1
Maximum31263052
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:35.994571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4224.5
Q1152482
median684210.5
Q33063615.2
95-th percentile10682847
Maximum31263052
Range31263051
Interquartile range (IQR)2911133.2

Descriptive statistics

Standard deviation4081663.5
Coefficient of variation (CV)1.6581715
Kurtosis12.456732
Mean2461544.9
Median Absolute Deviation (MAD)665648
Skewness3.0980555
Sum9.4671017 × 109
Variance1.6659977 × 1013
MonotonicityNot monotonic
2025-02-08T16:18:36.058178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
73272 2
 
< 0.1%
292254 2
 
< 0.1%
26 2
 
< 0.1%
293 2
 
< 0.1%
211 2
 
< 0.1%
111 2
 
< 0.1%
50 2
 
< 0.1%
563 2
 
< 0.1%
697 2
 
< 0.1%
811 2
 
< 0.1%
Other values (3826) 3826
38.3%
(Missing) 6154
61.5%
ValueCountFrequency (%)
1 1
< 0.1%
8 1
< 0.1%
13 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
26 2
< 0.1%
29 1
< 0.1%
31 1
< 0.1%
33 1
< 0.1%
36 1
< 0.1%
ValueCountFrequency (%)
31263052 1
< 0.1%
30836351 1
< 0.1%
30688612 1
< 0.1%
30489054 1
< 0.1%
30186461 1
< 0.1%
29905570 1
< 0.1%
29597609 1
< 0.1%
29335166 1
< 0.1%
29014550 1
< 0.1%
28823897 1
< 0.1%

total_tests_per_thousand
Real number (ℝ)

High correlation  Missing 

Distinct3741
Distinct (%)97.3%
Missing6154
Missing (%)61.5%
Infinite0
Infinite (%)0.0%
Mean288.26654
Minimum0
Maximum3471.204
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:36.119745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.41675
Q116.86975
median84.1605
Q3304.125
95-th percentile1366.1265
Maximum3471.204
Range3471.204
Interquartile range (IQR)287.25525

Descriptive statistics

Standard deviation498.14909
Coefficient of variation (CV)1.728085
Kurtosis10.102584
Mean288.26654
Median Absolute Deviation (MAD)80.1005
Skewness2.9621998
Sum1108673.1
Variance248152.52
MonotonicityNot monotonic
2025-02-08T16:18:36.184745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001 12
 
0.1%
0.011 8
 
0.1%
0.003 7
 
0.1%
0.01 7
 
0.1%
0.002 7
 
0.1%
0.012 7
 
0.1%
0.006 6
 
0.1%
0.004 6
 
0.1%
0.009 5
 
0.1%
0.007 5
 
0.1%
Other values (3731) 3776
37.8%
(Missing) 6154
61.5%
ValueCountFrequency (%)
0 1
 
< 0.1%
0.001 12
0.1%
0.002 7
0.1%
0.003 7
0.1%
0.004 6
0.1%
0.005 2
 
< 0.1%
0.006 6
0.1%
0.007 5
0.1%
0.008 3
 
< 0.1%
0.009 5
0.1%
ValueCountFrequency (%)
3471.204 1
< 0.1%
3423.827 1
< 0.1%
3407.423 1
< 0.1%
3385.265 1
< 0.1%
3351.668 1
< 0.1%
3320.48 1
< 0.1%
3286.286 1
< 0.1%
3257.147 1
< 0.1%
3221.548 1
< 0.1%
3200.379 1
< 0.1%

new_tests_per_thousand
Real number (ℝ)

High correlation  Missing  Skewed 

Distinct2071
Distinct (%)58.4%
Missing6453
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean2.3698424
Minimum0
Maximum327.086
Zeros48
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:36.246745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.026
Q10.146
median0.77
Q32.0995
95-th percentile7.9366
Maximum327.086
Range327.086
Interquartile range (IQR)1.9535

Descriptive statistics

Standard deviation7.4988918
Coefficient of variation (CV)3.1642998
Kurtosis1000.149
Mean2.3698424
Median Absolute Deviation (MAD)0.681
Skewness24.758304
Sum8405.831
Variance56.233379
MonotonicityNot monotonic
2025-02-08T16:18:36.309741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48
 
0.5%
0.001 28
 
0.3%
0.086 22
 
0.2%
0.078 18
 
0.2%
0.077 18
 
0.2%
0.085 16
 
0.2%
0.08 14
 
0.1%
0.083 13
 
0.1%
0.09 13
 
0.1%
0.067 13
 
0.1%
Other values (2061) 3344
33.4%
(Missing) 6453
64.5%
ValueCountFrequency (%)
0 48
0.5%
0.001 28
0.3%
0.002 11
 
0.1%
0.003 9
 
0.1%
0.004 5
 
0.1%
0.005 4
 
< 0.1%
0.006 6
 
0.1%
0.007 5
 
0.1%
0.008 1
 
< 0.1%
0.009 1
 
< 0.1%
ValueCountFrequency (%)
327.086 1
< 0.1%
67.746 1
< 0.1%
57.365 1
< 0.1%
56.102 1
< 0.1%
53.921 1
< 0.1%
53.634 1
< 0.1%
48.483 1
< 0.1%
47.378 1
< 0.1%
46.448 1
< 0.1%
43.958 1
< 0.1%

new_tests_smoothed
Real number (ℝ)

High correlation  Missing 

Distinct3959
Distinct (%)86.8%
Missing5439
Missing (%)54.4%
Infinite0
Infinite (%)0.0%
Mean18750.538
Minimum0
Maximum539742
Zeros10
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-02-08T16:18:36.373745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile198
Q11688
median8510
Q320247
95-th percentile55506
Maximum539742
Range539742
Interquartile range (IQR)18559

Descriptive statistics

Standard deviation41372.356
Coefficient of variation (CV)2.2064623
Kurtosis49.851189
Mean18750.538
Median Absolute Deviation (MAD)7365
Skewness6.3166074
Sum85521204
Variance1.7116718 × 109
MonotonicityNot monotonic
2025-02-08T16:18:36.437745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
0.1%
5 10
 
0.1%
341 8
 
0.1%
22469 8
 
0.1%
4 8
 
0.1%
1 7
 
0.1%
8 6
 
0.1%
6 6
 
0.1%
1370 5
 
0.1%
222 5
 
0.1%
Other values (3949) 4488
44.9%
(Missing) 5439
54.4%
ValueCountFrequency (%)
0 10
0.1%
1 7
0.1%
2 3
 
< 0.1%
3 3
 
< 0.1%
4 8
0.1%
5 10
0.1%
6 6
0.1%
7 1
 
< 0.1%
8 6
0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
539742 1
< 0.1%
526470 1
< 0.1%
521061 1
< 0.1%
512583 1
< 0.1%
504579 1
< 0.1%
451220 1
< 0.1%
436700 1
< 0.1%
329198 1
< 0.1%
321002 1
< 0.1%
319968 1
< 0.1%

Interactions

2025-02-08T16:18:30.709127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:58.549775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.210499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.914537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.269544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.667814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.231580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.547580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.025622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.370129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.934464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.321770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.650658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.112655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.383683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.833152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.114158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.442497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.882490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.940512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.253553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.525494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.952786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.278789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.764067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:58.618776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.268494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.973547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.336066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.734816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.288579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.610574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.084617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.575117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.992471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.381770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.709658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.165658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.436675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.885157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.167157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.496496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.927288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.988512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.304494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.578496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.006785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.333790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.817060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:58.684769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.323494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.025542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.385721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.023808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.340581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.810616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.145617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.630169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.047469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.433764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.762658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.220661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.491676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.937158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.221157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.693491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.972338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.042513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.358489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.633494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.063789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.385789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.873061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:58.755772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.377493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.077543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.453811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.082813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.393580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.867011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.200623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.688112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.099060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.489766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.818659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.271659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.550680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.994157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.278152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.749490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.017855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.093513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.409489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.689495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.120784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.441175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.927066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:58.846770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.431500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.130544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.506807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.137814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.448579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.921623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.258618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.743149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.155228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.544766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.871659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.326654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.605675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.046157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.333156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.802496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.060517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.142512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.465490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.742489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.177786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.494214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.983065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:58.953274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.486495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.183543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.559813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.190815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.499573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.978623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.313622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.798471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.203228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.599771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.924660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.385576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.659674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.100157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.387152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.856491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.102513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.190511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.520490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.799489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.232843image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.686066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.039065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.015895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.546500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.238539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.619814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.243816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.549578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.033622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.371618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.858467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.252773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.653770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.977658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.445455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.715674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.153158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.446152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.913494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.145514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.375513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.579490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.987488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.292791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.741060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.094059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.078496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.608501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.295543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.675807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.299813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.608574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.092627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.433616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.919531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.307766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.712770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.034654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.500071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.768682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.206156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.499156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.966496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.185586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.421512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.633490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.044496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.349789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.795065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.145067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.140499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.666495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.355538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.733814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.354813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.664578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.150622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.493622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.981467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.363770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.771766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.094658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.560680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.822680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.257153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.553154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.019497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.231516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.470517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.685489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.093489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.402789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.846061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.201065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.204497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.728495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.413543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.791814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.413814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.720578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.212623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.554625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.041466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.419770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.831832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.152658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.618680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.879679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.315157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.616152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.076491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.276513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.519519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.743490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.151494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.460790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.904061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.253065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.261498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.815499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.466545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.848810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.468079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.771587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.266618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.610624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.097471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.467771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.887771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.204659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.671681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.932675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.366157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.669160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.129495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.327512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.564587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.797494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.202494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.514789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.956065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.307070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.322498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.885496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.521543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.903814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.528869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.826579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.324622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.668623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.157467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.524772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.942772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.259654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.726682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.987680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.417152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.728225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.181495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.378516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.611590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.852494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.261736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.570789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.011061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.361065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.381501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.962499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.576537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.970814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.582482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.880579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.382622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.729618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.216467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.575774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.998773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.315653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.784681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.042680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.472152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.785925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.237489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.421517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.661587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.906494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.315726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.628791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.066061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.411059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.438494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.031499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.630542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.026814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.637574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.939575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.440624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.787617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.274467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.625770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.051770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.371653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.835690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.094682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.524153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.841924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.291496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.459517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.704587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.956496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.366221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.681789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.118060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.467067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.517496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.109502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.688538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.088812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.694574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.996580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.494622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.848376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.333470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.679774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.106765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.431658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.887680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.148681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.582155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.898491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.347497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.501517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.753587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.013498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.423852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.738789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.173061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.520065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.590495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.179538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.754538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.146811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.748578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.053574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.548622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.900962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.408468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.730774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.158766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.487656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.938676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.203676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.633157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.954495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.402491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.545513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.800587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.065494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.478792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.793789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.228061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.573065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.658495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.247538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.813600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.205809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.803572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.111576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.600623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:09.958542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.481470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.783770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.214477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.548659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.991682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.259680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.688158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.009490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.459491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.593511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.852587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.121488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.532789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.851784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.283061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.631385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.727493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.308539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.874544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.261807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.858579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.167577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.653621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.009544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.540475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.835766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.269079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.606655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.043680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.315675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.741151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.065497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.512494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.637513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.900584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.174496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.587785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.906790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.339064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.677385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.788495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.363543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.921538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.303808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.901578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.209577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.695626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.054611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.585470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.879771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.310073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.652662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.081676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.361676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.785157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.108491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.557490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.676517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.950582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.213495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.630790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:28.950789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.384068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.727999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.852498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.427536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:02.979545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.355810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:05.948580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.259579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.741617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.105610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.636472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.927771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.357656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.702653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.127684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.412677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.835151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.159489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.609496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.722512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:24.999587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.259497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.681786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.000784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.436065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.781699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.916498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.498539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.036544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.422811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.004579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.316580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.796623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.156124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.697472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:12.981767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.413655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.758659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.176682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.467678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.890153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.214489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.664495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.762512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.046581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.310489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.733785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.056791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.489065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.838280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:17:59.973495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.573545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.092541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.486809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.063579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.375582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.853625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.210123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.755471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.033771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.469654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.811653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.226674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.526681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:19.948157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.270491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.719495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.805512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.098359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.364494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.787792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.111786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.546068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.892209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.076495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.649538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.149541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.545814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.120579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.432573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.914622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.263127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.817472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.085766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.534658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:15.866661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.281675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.587003image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.005157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.329495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.774491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.848512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.145904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.419494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.844790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.170850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.601058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:31.945254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:00.150497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:01.708543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:03.204545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:04.610808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:06.174578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:07.490582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:08.967624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:10.316128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:11.874472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:13.269771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:14.592654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:16.056655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:17.331680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:18.780157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:20.059157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:21.387497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:22.830554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:23.894513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:25.199904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:26.472494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:27.897791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:29.225792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-08T16:18:30.653061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-02-08T16:18:36.503746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
total_casesnew_casesnew_cases_smoothedtotal_deathsnew_deathsnew_deaths_smoothedtotal_cases_per_millionnew_cases_per_millionnew_cases_smoothed_per_milliontotal_deaths_per_millionnew_deaths_per_millionnew_deaths_smoothed_per_millionreproduction_rateicu_patientsicu_patients_per_millionhosp_patientshosp_patients_per_millionweekly_icu_admissionsweekly_icu_admissions_per_millionweekly_hosp_admissionsweekly_hosp_admissions_per_millionnew_teststotal_teststotal_tests_per_thousandnew_tests_per_thousandnew_tests_smoothed
total_cases1.0000.8580.8660.9900.8180.828-0.032-0.034-0.043-0.038-0.036-0.042-0.0160.5000.5030.4250.421NaNNaN0.2690.2690.1660.4090.0780.0470.245
new_cases0.8581.0000.9970.8310.9220.911-0.041-0.013-0.022-0.051-0.024-0.0300.0640.5080.5190.5890.600NaNNaN0.6530.6530.1320.243-0.0100.0170.188
new_cases_smoothed0.8660.9971.0000.8410.9340.927-0.043-0.017-0.022-0.052-0.024-0.0290.0380.6110.6240.6940.706NaNNaN0.7290.7290.1300.254-0.0070.0150.196
total_deaths0.9900.8310.8411.0000.8300.846-0.040-0.045-0.054-0.016-0.032-0.043-0.0120.3840.3320.3330.277NaNNaN0.0170.0170.1210.3450.0030.0030.190
new_deaths0.8180.9220.9340.8301.0000.985-0.070-0.038-0.047-0.0610.0420.001-0.0200.8060.7910.8340.820NaNNaN0.6790.6790.0470.078-0.085-0.0290.070
new_deaths_smoothed0.8280.9110.9270.8460.9851.000-0.062-0.036-0.042-0.0610.0030.011-0.0410.8320.8150.8510.836NaNNaN0.6420.6420.0630.125-0.089-0.0360.103
total_cases_per_million-0.032-0.041-0.043-0.040-0.070-0.0621.0000.5700.6910.7880.2690.386-0.0680.4860.5100.4060.421NaNNaN0.2690.2690.2410.3960.7010.3140.185
new_cases_per_million-0.034-0.013-0.017-0.045-0.038-0.0360.5701.0000.8360.4410.4360.4440.0800.4970.5260.5770.607NaNNaN0.6530.6530.1800.2280.4190.2280.149
new_cases_smoothed_per_million-0.043-0.022-0.022-0.054-0.047-0.0420.6910.8361.0000.5350.4210.5560.0520.5960.6280.6790.712NaNNaN0.7290.7290.1790.2310.4500.2300.156
total_deaths_per_million-0.038-0.051-0.052-0.016-0.061-0.0610.7880.4410.5351.0000.3320.470-0.0930.3910.3520.3320.288NaNNaN0.0170.0170.2130.4080.3160.1680.248
new_deaths_per_million-0.036-0.024-0.024-0.0320.0420.0030.2690.4360.4210.3321.0000.729-0.0610.7970.7970.8300.831NaNNaN0.6790.6790.0700.0540.0280.0500.060
new_deaths_smoothed_per_million-0.042-0.030-0.029-0.0430.0010.0110.3860.4440.5560.4700.7291.000-0.1170.8250.8250.8480.849NaNNaN0.6420.6420.0900.1020.0680.0590.099
reproduction_rate-0.0160.0640.038-0.012-0.020-0.041-0.0680.0800.052-0.093-0.061-0.1171.000-0.231-0.254-0.191-0.209NaNNaN-0.070-0.070-0.018-0.074-0.113-0.049-0.045
icu_patients0.5000.5080.6110.3840.8060.8320.4860.4970.5960.3910.7970.825-0.2311.0000.9880.9710.955NaNNaN0.9030.9030.0780.2820.2400.0660.124
icu_patients_per_million0.5030.5190.6240.3320.7910.8150.5100.5260.6280.3520.7970.825-0.2540.9881.0000.9590.966NaNNaN0.9030.9030.1290.3430.3120.1200.201
hosp_patients0.4250.5890.6940.3330.8340.8510.4060.5770.6790.3320.8300.848-0.1910.9710.9591.0000.988NaNNaN0.9480.9480.0290.1580.1180.0170.043
hosp_patients_per_million0.4210.6000.7060.2770.8200.8360.4210.6070.7120.2880.8310.849-0.2090.9550.9660.9881.000NaNNaN0.9480.9480.0670.1940.1640.0570.099
weekly_icu_admissionsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
weekly_icu_admissions_per_millionNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
weekly_hosp_admissions0.2690.6530.7290.0170.6790.6420.2690.6530.7290.0170.6790.642-0.0700.9030.9030.9480.948NaNNaN1.0001.0000.2490.2000.2000.2490.301
weekly_hosp_admissions_per_million0.2690.6530.7290.0170.6790.6420.2690.6530.7290.0170.6790.642-0.0700.9030.9030.9480.948NaNNaN1.0001.0000.2490.2000.2000.2490.301
new_tests0.1660.1320.1300.1210.0470.0630.2410.1800.1790.2130.0700.090-0.0180.0780.1290.0290.067NaNNaN0.2490.2491.0000.5480.4250.9510.695
total_tests0.4090.2430.2540.3450.0780.1250.3960.2280.2310.4080.0540.102-0.0740.2820.3430.1580.194NaNNaN0.2000.2000.5481.0000.6250.4580.769
total_tests_per_thousand0.078-0.010-0.0070.003-0.085-0.0890.7010.4190.4500.3160.0280.068-0.1130.2400.3120.1180.164NaNNaN0.2000.2000.4250.6251.0000.5510.573
new_tests_per_thousand0.0470.0170.0150.003-0.029-0.0360.3140.2280.2300.1680.0500.059-0.0490.0660.1200.0170.057NaNNaN0.2490.2490.9510.4580.5511.0000.636
new_tests_smoothed0.2450.1880.1960.1900.0700.1030.1850.1490.1560.2480.0600.099-0.0450.1240.2010.0430.099NaNNaN0.3010.3010.6950.7690.5730.6361.000
2025-02-08T16:18:36.672745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
total_casesnew_casesnew_cases_smoothedtotal_deathsnew_deathsnew_deaths_smoothedtotal_cases_per_millionnew_cases_per_millionnew_cases_smoothed_per_milliontotal_deaths_per_millionnew_deaths_per_millionnew_deaths_smoothed_per_millionreproduction_rateicu_patientsicu_patients_per_millionhosp_patientshosp_patients_per_millionweekly_icu_admissionsweekly_icu_admissions_per_millionweekly_hosp_admissionsweekly_hosp_admissions_per_millionnew_teststotal_teststotal_tests_per_thousandnew_tests_per_thousandnew_tests_smoothed
total_cases1.0000.8710.9030.9600.8080.8560.6080.5450.4950.4850.5840.562-0.0160.6040.5810.5900.572NaNNaN0.3250.3250.6830.7710.3570.1930.656
new_cases0.8711.0000.9690.8150.8990.9070.4300.6820.5380.2860.6710.5860.2320.7500.7530.7580.766NaNNaN0.7740.7740.6210.5380.1180.1020.547
new_cases_smoothed0.9030.9691.0000.8420.8990.9320.4550.6210.5790.3130.6670.6230.2040.8070.8090.8090.819NaNNaN0.7850.7850.6230.5480.1250.0980.557
total_deaths0.9600.8150.8421.0000.8190.8520.4320.3760.3190.4820.5530.446-0.0390.4710.4060.4760.414NaNNaN0.3250.3250.5630.6260.2180.0840.552
new_deaths0.8080.8990.8990.8191.0000.9550.2380.4320.3430.2390.7540.5240.0430.9000.8920.9270.924NaNNaN0.8280.8280.3830.298-0.097-0.1160.325
new_deaths_smoothed0.8560.9070.9320.8520.9551.0000.3540.4950.4400.2680.6930.6650.0430.9090.8990.9360.932NaNNaN0.7870.7870.4830.409-0.056-0.0910.418
total_cases_per_million0.6080.4300.4550.4320.2380.3541.0000.7360.8450.9380.5160.705-0.1170.5810.5670.5540.546NaNNaN0.3250.3250.4750.5980.6680.5410.340
new_cases_per_million0.5450.6820.6210.3760.4320.4950.7361.0000.8780.6260.6930.7540.1830.7330.7460.7350.755NaNNaN0.7740.7740.4100.3690.4410.4700.244
new_cases_smoothed_per_million0.4950.5380.5790.3190.3430.4400.8450.8781.0000.7410.6320.8000.1350.7890.8030.7860.809NaNNaN0.7850.7850.3980.3640.4610.4770.229
total_deaths_per_million0.4850.2860.3130.4820.2390.2680.9380.6260.7411.0000.4950.659-0.1460.5290.4820.5070.463NaNNaN0.3250.3250.3630.4650.5340.4140.220
new_deaths_per_million0.5840.6710.6670.5530.7540.6930.5160.6930.6320.4951.0000.7860.0290.8930.8940.9150.922NaNNaN0.8280.8280.1850.1490.1810.2020.101
new_deaths_smoothed_per_million0.5620.5860.6230.4460.5240.6650.7050.7540.8000.6590.7861.000-0.0110.9040.9040.9240.931NaNNaN0.7870.7870.3220.2840.2270.2140.186
reproduction_rate-0.0160.2320.204-0.0390.0430.043-0.1170.1830.135-0.1460.029-0.0111.000-0.321-0.334-0.281-0.296NaNNaN-0.140-0.140-0.035-0.157-0.225-0.135-0.072
icu_patients0.6040.7500.8070.4710.9000.9090.5810.7330.7890.5290.8930.904-0.3211.0000.9920.9780.980NaNNaN0.9470.9470.4970.4710.4630.4740.521
icu_patients_per_million0.5810.7530.8090.4060.8920.8990.5670.7460.8030.4820.8940.904-0.3340.9921.0000.9630.979NaNNaN0.9470.9470.5060.4770.4760.4900.525
hosp_patients0.5900.7580.8090.4760.9270.9360.5540.7350.7860.5070.9150.924-0.2810.9780.9631.0000.991NaNNaN0.9520.9520.4670.4260.4170.4460.484
hosp_patients_per_million0.5720.7660.8190.4140.9240.9320.5460.7550.8090.4630.9220.931-0.2960.9800.9790.9911.000NaNNaN0.9520.9520.4830.4380.4360.4690.493
weekly_icu_admissionsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
weekly_icu_admissions_per_millionNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
weekly_hosp_admissions0.3250.7740.7850.3250.8280.7870.3250.7740.7850.3250.8280.787-0.1400.9470.9470.9520.952NaNNaN1.0001.0000.3850.3250.3250.3850.392
weekly_hosp_admissions_per_million0.3250.7740.7850.3250.8280.7870.3250.7740.7850.3250.8280.787-0.1400.9470.9470.9520.952NaNNaN1.0001.0000.3850.3250.3250.3850.392
new_tests0.6830.6210.6230.5630.3830.4830.4750.4100.3980.3630.1850.322-0.0350.4970.5060.4670.483NaNNaN0.3850.3851.0000.9110.5250.5480.980
total_tests0.7710.5380.5480.6260.2980.4090.5980.3690.3640.4650.1490.284-0.1570.4710.4770.4260.438NaNNaN0.3250.3250.9111.0000.6780.5490.925
total_tests_per_thousand0.3570.1180.1250.218-0.097-0.0560.6680.4410.4610.5340.1810.227-0.2250.4630.4760.4170.436NaNNaN0.3250.3250.5250.6781.0000.9100.521
new_tests_per_thousand0.1930.1020.0980.084-0.116-0.0910.5410.4700.4770.4140.2020.214-0.1350.4740.4900.4460.469NaNNaN0.3850.3850.5480.5490.9101.0000.513
new_tests_smoothed0.6560.5470.5570.5520.3250.4180.3400.2440.2290.2200.1010.186-0.0720.5210.5250.4840.493NaNNaN0.3920.3920.9800.9250.5210.5131.000
2025-02-08T16:18:36.980746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
total_casesnew_casesnew_cases_smoothedtotal_deathsnew_deathsnew_deaths_smoothedtotal_cases_per_millionnew_cases_per_millionnew_cases_smoothed_per_milliontotal_deaths_per_millionnew_deaths_per_millionnew_deaths_smoothed_per_millionreproduction_rateicu_patientsicu_patients_per_millionhosp_patientshosp_patients_per_millionweekly_icu_admissionsweekly_icu_admissions_per_millionweekly_hosp_admissionsweekly_hosp_admissions_per_millionnew_teststotal_teststotal_tests_per_thousandnew_tests_per_thousandnew_tests_smoothed
total_cases1.0000.6920.7290.8460.6380.6790.4500.3760.3390.3510.4120.395-0.0140.4310.3970.4210.389NaNNaN0.2220.2220.5060.6080.2760.1410.484
new_cases0.6921.0000.8860.6290.7600.7590.2970.5250.3870.1970.4900.4290.1560.5500.5480.5600.566NaNNaN0.5880.5880.4610.3840.0810.0760.416
new_cases_smoothed0.7290.8861.0000.6580.7550.7900.3090.4530.4250.2120.4850.4570.1380.6190.6170.6220.633NaNNaN0.6290.6290.4600.3930.0850.0700.426
total_deaths0.8460.6290.6581.0000.6550.6770.3050.2530.2110.3440.3880.305-0.0290.3140.2650.3120.262NaNNaN0.2240.2240.4010.4710.1870.0630.390
new_deaths0.6380.7600.7550.6551.0000.8730.1660.3160.2470.1690.5890.3970.0300.7350.7200.7730.766NaNNaN0.6490.6490.2710.207-0.064-0.0680.235
new_deaths_smoothed0.6790.7590.7900.6770.8731.0000.2390.3500.3080.1810.5160.5110.0280.7470.7270.7790.770NaNNaN0.5930.5930.3420.284-0.037-0.0550.300
total_cases_per_million0.4500.2970.3090.3050.1660.2391.0000.5610.6490.7940.3900.526-0.0770.4220.3960.3910.373NaNNaN0.2220.2220.3450.4570.5350.3910.247
new_cases_per_million0.3760.5250.4530.2530.3160.3500.5611.0000.7840.4590.5810.6180.1210.5330.5430.5360.555NaNNaN0.5880.5880.2910.2590.3130.3490.178
new_cases_smoothed_per_million0.3390.3870.4250.2110.2470.3080.6490.7841.0000.5400.5170.6450.0860.6000.6130.5990.621NaNNaN0.6290.6290.2850.2610.3280.3500.175
total_deaths_per_million0.3510.1970.2120.3440.1690.1810.7940.4590.5401.0000.3770.490-0.1010.3700.3280.3590.317NaNNaN0.2240.2240.2560.3520.4230.3100.155
new_deaths_per_million0.4120.4900.4850.3880.5890.5160.3900.5810.5170.3771.0000.7130.0170.7240.7230.7530.762NaNNaN0.6490.6490.1280.1000.1310.1560.076
new_deaths_smoothed_per_million0.3950.4290.4570.3050.3970.5110.5260.6180.6450.4900.7131.000-0.0130.7390.7370.7630.770NaNNaN0.5930.5930.2200.1900.1570.1580.130
reproduction_rate-0.0140.1560.138-0.0290.0300.028-0.0770.1210.086-0.1010.017-0.0131.000-0.215-0.225-0.193-0.209NaNNaN-0.099-0.099-0.024-0.101-0.151-0.092-0.049
icu_patients0.4310.5500.6190.3140.7350.7470.4220.5330.6000.3700.7240.739-0.2151.0000.9430.8850.886NaNNaN0.8200.8200.3360.3360.3320.3210.366
icu_patients_per_million0.3970.5480.6170.2650.7200.7270.3960.5430.6130.3280.7230.737-0.2250.9431.0000.8500.880NaNNaN0.8200.8200.3480.3390.3420.3400.375
hosp_patients0.4210.5600.6220.3120.7730.7790.3910.5360.5990.3590.7530.763-0.1930.8850.8501.0000.943NaNNaN0.8270.8270.3010.2820.2730.2870.329
hosp_patients_per_million0.3890.5660.6330.2620.7660.7700.3730.5550.6210.3170.7620.770-0.2090.8860.8800.9431.000NaNNaN0.8270.8270.3180.2860.2880.3110.343
weekly_icu_admissionsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
weekly_icu_admissions_per_millionNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
weekly_hosp_admissions0.2220.5880.6290.2240.6490.5930.2220.5880.6290.2240.6490.593-0.0990.8200.8200.8270.827NaNNaN1.0001.0000.3030.2220.2220.3030.320
weekly_hosp_admissions_per_million0.2220.5880.6290.2240.6490.5930.2220.5880.6290.2240.6490.593-0.0990.8200.8200.8270.827NaNNaN1.0001.0000.3030.2220.2220.3030.320
new_tests0.5060.4610.4600.4010.2710.3420.3450.2910.2850.2560.1280.220-0.0240.3360.3480.3010.318NaNNaN0.3030.3031.0000.7380.3780.4180.892
total_tests0.6080.3840.3930.4710.2070.2840.4570.2590.2610.3520.1000.190-0.1010.3360.3390.2820.286NaNNaN0.2220.2220.7381.0000.5140.4010.762
total_tests_per_thousand0.2760.0810.0850.187-0.064-0.0370.5350.3130.3280.4230.1310.157-0.1510.3320.3420.2730.288NaNNaN0.2220.2220.3780.5141.0000.7450.377
new_tests_per_thousand0.1410.0760.0700.063-0.068-0.0550.3910.3490.3500.3100.1560.158-0.0920.3210.3400.2870.311NaNNaN0.3030.3030.4180.4010.7451.0000.376
new_tests_smoothed0.4840.4160.4260.3900.2350.3000.2470.1780.1750.1550.0760.130-0.0490.3660.3750.3290.343NaNNaN0.3200.3200.8920.7620.3770.3761.000
2025-02-08T16:18:37.153745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
iso_codecontinentlocationtotal_casesnew_casesnew_cases_smoothedtotal_deathsnew_deathsnew_deaths_smoothedtotal_cases_per_millionnew_cases_per_millionnew_cases_smoothed_per_milliontotal_deaths_per_millionnew_deaths_per_millionnew_deaths_smoothed_per_millionreproduction_rateicu_patientsicu_patients_per_millionhosp_patientshosp_patients_per_millionweekly_hosp_admissionsweekly_hosp_admissions_per_millionnew_teststotal_teststotal_tests_per_thousandnew_tests_per_thousandnew_tests_smoothed
iso_code1.0001.0001.0000.5770.5880.5930.6250.5970.6110.6680.3850.5590.7390.3600.5230.4980.4980.3780.4950.372NaNNaN0.2970.5310.5850.2970.463
continent1.0001.0001.000NaNNaNNaN0.3880.1300.1270.3580.1860.3260.4750.1830.3580.290NaNNaNNaNNaNNaNNaN0.1610.4640.3660.1610.358
location1.0001.0001.0000.5770.5880.5930.6250.5970.6110.6680.3850.5590.7390.3600.5230.4980.4980.3780.4950.372NaNNaN0.2970.5310.5850.2970.463
total_cases0.577NaN0.5771.0000.9580.9650.9890.9320.9430.0390.0000.0000.0870.0000.040NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
new_cases0.588NaN0.5880.9581.0000.9830.9280.9560.9420.0190.0000.0000.0750.0000.020NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
new_cases_smoothed0.593NaN0.5930.9650.9831.0000.9290.9670.9800.0250.0000.0000.0760.0000.023NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
total_deaths0.6250.3880.6250.9890.9280.9291.0000.9210.9230.1410.0000.1080.2530.0000.0660.113NaNNaNNaNNaNNaNNaN0.0000.6390.0690.0000.000
new_deaths0.5970.1300.5970.9320.9560.9670.9211.0000.9820.0580.0000.0290.0970.3240.1400.0000.2460.2460.2540.254NaNNaN0.0000.0000.0000.0000.000
new_deaths_smoothed0.6110.1270.6110.9430.9420.9800.9230.9821.0000.0520.0000.0150.1000.0170.0980.026NaNNaNNaNNaNNaNNaN0.0000.0000.0000.0000.000
total_cases_per_million0.6680.3580.6680.0390.0190.0250.1410.0580.0521.0000.5740.7600.8970.2640.5710.2590.8950.8530.8750.8930.7860.7860.1990.6650.8320.1990.335
new_cases_per_million0.3850.1860.3850.0000.0000.0000.0000.0000.0000.5741.0000.8200.4450.5920.4620.1060.4530.4360.5240.5170.5740.5740.0130.1850.3650.0130.172
new_cases_smoothed_per_million0.5590.3260.5590.0000.0000.0000.1080.0290.0150.7600.8201.0000.6380.3570.6440.1990.7890.7800.8330.8270.7940.7940.1530.4850.6640.1530.289
total_deaths_per_million0.7390.4750.7390.0870.0750.0760.2530.0970.1000.8970.4450.6381.0000.3390.6630.2750.8670.8450.8750.8730.8660.8660.2030.7710.7100.2030.355
new_deaths_per_million0.3600.1830.3600.0000.0000.0000.0000.3240.0170.2640.5920.3570.3391.0000.6460.0670.6660.6630.6980.7010.9830.9830.0000.1070.1140.0000.000
new_deaths_smoothed_per_million0.5230.3580.5230.0400.0200.0230.0660.1400.0980.5710.4620.6440.6630.6461.0000.2310.8900.8870.8790.8800.9330.9330.1570.4380.4290.1570.226
reproduction_rate0.4980.2900.498NaNNaNNaN0.1130.0000.0260.2590.1060.1990.2750.0670.2311.0000.4500.4800.3970.4190.4400.4400.0000.1720.2920.0000.125
icu_patients0.498NaN0.498NaNNaNNaNNaN0.246NaN0.8950.4530.7890.8670.6660.8900.4501.0000.9900.9620.9580.7930.7930.2470.7980.7870.2470.463
icu_patients_per_million0.378NaN0.378NaNNaNNaNNaN0.246NaN0.8530.4360.7800.8450.6630.8870.4800.9901.0000.9570.9560.7930.7930.2290.8260.8140.2290.481
hosp_patients0.495NaN0.495NaNNaNNaNNaN0.254NaN0.8750.5240.8330.8750.6980.8790.3970.9620.9571.0000.9910.8980.8980.2050.7920.7920.2050.510
hosp_patients_per_million0.372NaN0.372NaNNaNNaNNaN0.254NaN0.8930.5170.8270.8730.7010.8800.4190.9580.9560.9911.0000.8980.8980.2310.8040.7850.2310.464
weekly_hosp_admissionsNaNNaNNaNNaNNaNNaNNaNNaNNaN0.7860.5740.7940.8660.9830.9330.4400.7930.7930.8980.8981.0001.000NaN0.7480.592NaN0.357
weekly_hosp_admissions_per_millionNaNNaNNaNNaNNaNNaNNaNNaNNaN0.7860.5740.7940.8660.9830.9330.4400.7930.7930.8980.8981.0001.000NaN0.7480.592NaN0.357
new_tests0.2970.1610.297NaNNaNNaN0.0000.0000.0000.1990.0130.1530.2030.0000.1570.0000.2470.2290.2050.231NaNNaN1.0000.5690.5121.0000.731
total_tests0.5310.4640.531NaNNaNNaN0.6390.0000.0000.6650.1850.4850.7710.1070.4380.1720.7980.8260.7920.8040.7480.7480.5691.0000.9580.5690.714
total_tests_per_thousand0.5850.3660.585NaNNaNNaN0.0690.0000.0000.8320.3650.6640.7100.1140.4290.2920.7870.8140.7920.7850.5920.5920.5120.9581.0000.5120.667
new_tests_per_thousand0.2970.1610.297NaNNaNNaN0.0000.0000.0000.1990.0130.1530.2030.0000.1570.0000.2470.2290.2050.231NaNNaN1.0000.5690.5121.0000.731
new_tests_smoothed0.4630.3580.463NaNNaNNaN0.0000.0000.0000.3350.1720.2890.3550.0000.2260.1250.4630.4810.5100.4640.3570.3570.7310.7140.6670.7311.000
2025-02-08T16:18:37.297745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
continentiso_codelocation
continent1.0000.9990.999
iso_code0.9991.0001.000
location0.9991.0001.000
2025-02-08T16:18:37.372750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
continenthosp_patientshosp_patients_per_millionicu_patientsicu_patients_per_millioniso_codelocationnew_casesnew_cases_per_millionnew_cases_smoothednew_cases_smoothed_per_millionnew_deathsnew_deaths_per_millionnew_deaths_smoothednew_deaths_smoothed_per_millionnew_testsnew_tests_per_thousandnew_tests_smoothedreproduction_ratetotal_casestotal_cases_per_milliontotal_deathstotal_deaths_per_milliontotal_teststotal_tests_per_thousandweekly_hosp_admissionsweekly_hosp_admissions_per_million
continent1.0001.0001.0001.0001.0000.9990.9991.0000.0991.0000.1780.0840.1090.0910.1970.0640.0640.2360.1571.0000.1970.2800.2730.2950.2261.0001.000
hosp_patients1.0001.0000.9910.9780.9630.3790.3790.7580.7350.8090.7860.9270.9150.9360.9240.4670.4460.484-0.2810.5900.5540.4760.5070.4260.4170.9520.952
hosp_patients_per_million1.0000.9911.0000.9800.9790.2840.2840.7660.7550.8190.8090.9240.9220.9320.9310.4830.4690.493-0.2960.5720.5460.4140.4630.4380.4360.9520.952
icu_patients1.0000.9780.9801.0000.9920.3790.3790.7500.7330.8070.7890.9000.8930.9090.9040.4970.4740.521-0.3210.6040.5810.4710.5290.4710.4630.9470.947
icu_patients_per_million1.0000.9630.9790.9921.0000.2890.2890.7530.7460.8090.8030.8920.8940.8990.9040.5060.4900.525-0.3340.5810.5670.4060.4820.4770.4760.9470.947
iso_code0.9990.3790.2840.3790.2891.0001.0000.2610.1520.2640.2430.2670.1640.2760.2220.1410.1410.2160.2070.2540.3180.2860.3820.2520.2881.0001.000
location0.9990.3790.2840.3790.2891.0001.0000.2610.1520.2640.2430.2670.1640.2760.2220.1410.1410.2160.2070.2540.3180.2860.3820.2520.2881.0001.000
new_cases1.0000.7580.7660.7500.7530.2610.2611.0000.6820.9690.5380.8990.6710.9070.5860.6210.1020.5470.2320.8710.4300.8150.2860.5380.1180.7740.774
new_cases_per_million0.0990.7350.7550.7330.7460.1520.1520.6821.0000.6210.8780.4320.6930.4950.7540.4100.4700.2440.1830.5450.7360.3760.6260.3690.4410.7740.774
new_cases_smoothed1.0000.8090.8190.8070.8090.2640.2640.9690.6211.0000.5790.8990.6670.9320.6230.6230.0980.5570.2040.9030.4550.8420.3130.5480.1250.7850.785
new_cases_smoothed_per_million0.1780.7860.8090.7890.8030.2430.2430.5380.8780.5791.0000.3430.6320.4400.8000.3980.4770.2290.1350.4950.8450.3190.7410.3640.4610.7850.785
new_deaths0.0840.9270.9240.9000.8920.2670.2670.8990.4320.8990.3431.0000.7540.9550.5240.383-0.1160.3250.0430.8080.2380.8190.2390.298-0.0970.8280.828
new_deaths_per_million0.1090.9150.9220.8930.8940.1640.1640.6710.6930.6670.6320.7541.0000.6930.7860.1850.2020.1010.0290.5840.5160.5530.4950.1490.1810.8280.828
new_deaths_smoothed0.0910.9360.9320.9090.8990.2760.2760.9070.4950.9320.4400.9550.6931.0000.6650.483-0.0910.4180.0430.8560.3540.8520.2680.409-0.0560.7870.787
new_deaths_smoothed_per_million0.1970.9240.9310.9040.9040.2220.2220.5860.7540.6230.8000.5240.7860.6651.0000.3220.2140.186-0.0110.5620.7050.4460.6590.2840.2270.7870.787
new_tests0.0640.4670.4830.4970.5060.1410.1410.6210.4100.6230.3980.3830.1850.4830.3221.0000.5480.980-0.0350.6830.4750.5630.3630.9110.5250.3850.385
new_tests_per_thousand0.0640.4460.4690.4740.4900.1410.1410.1020.4700.0980.477-0.1160.202-0.0910.2140.5481.0000.513-0.1350.1930.5410.0840.4140.5490.9100.3850.385
new_tests_smoothed0.2360.4840.4930.5210.5250.2160.2160.5470.2440.5570.2290.3250.1010.4180.1860.9800.5131.000-0.0720.6560.3400.5520.2200.9250.5210.3920.392
reproduction_rate0.157-0.281-0.296-0.321-0.3340.2070.2070.2320.1830.2040.1350.0430.0290.043-0.011-0.035-0.135-0.0721.000-0.016-0.117-0.039-0.146-0.157-0.225-0.140-0.140
total_cases1.0000.5900.5720.6040.5810.2540.2540.8710.5450.9030.4950.8080.5840.8560.5620.6830.1930.656-0.0161.0000.6080.9600.4850.7710.3570.3250.325
total_cases_per_million0.1970.5540.5460.5810.5670.3180.3180.4300.7360.4550.8450.2380.5160.3540.7050.4750.5410.340-0.1170.6081.0000.4320.9380.5980.6680.3250.325
total_deaths0.2800.4760.4140.4710.4060.2860.2860.8150.3760.8420.3190.8190.5530.8520.4460.5630.0840.552-0.0390.9600.4321.0000.4820.6260.2180.3250.325
total_deaths_per_million0.2730.5070.4630.5290.4820.3820.3820.2860.6260.3130.7410.2390.4950.2680.6590.3630.4140.220-0.1460.4850.9380.4821.0000.4650.5340.3250.325
total_tests0.2950.4260.4380.4710.4770.2520.2520.5380.3690.5480.3640.2980.1490.4090.2840.9110.5490.925-0.1570.7710.5980.6260.4651.0000.6780.3250.325
total_tests_per_thousand0.2260.4170.4360.4630.4760.2880.2880.1180.4410.1250.461-0.0970.181-0.0560.2270.5250.9100.521-0.2250.3570.6680.2180.5340.6781.0000.3250.325
weekly_hosp_admissions1.0000.9520.9520.9470.9471.0001.0000.7740.7740.7850.7850.8280.8280.7870.7870.3850.3850.392-0.1400.3250.3250.3250.3250.3250.3251.0001.000
weekly_hosp_admissions_per_million1.0000.9520.9520.9470.9471.0001.0000.7740.7740.7850.7850.8280.8280.7870.7870.3850.3850.392-0.1400.3250.3250.3250.3250.3250.3251.0001.000

Missing values

2025-02-08T16:18:32.047256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-08T16:18:32.327439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-08T16:18:32.560440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

iso_codecontinentlocationdatetotal_casesnew_casesnew_cases_smoothedtotal_deathsnew_deathsnew_deaths_smoothedtotal_cases_per_millionnew_cases_per_millionnew_cases_smoothed_per_milliontotal_deaths_per_millionnew_deaths_per_millionnew_deaths_smoothed_per_millionreproduction_rateicu_patientsicu_patients_per_millionhosp_patientshosp_patients_per_millionweekly_icu_admissionsweekly_icu_admissions_per_millionweekly_hosp_admissionsweekly_hosp_admissions_per_millionnew_teststotal_teststotal_tests_per_thousandnew_tests_per_thousandnew_tests_smoothed
0AFGAsiaAfghanistan2020-02-241.01.0NaNNaNNaNNaN0.0260.026NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1AFGAsiaAfghanistan2020-02-251.00.0NaNNaNNaNNaN0.0260.000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2AFGAsiaAfghanistan2020-02-261.00.0NaNNaNNaNNaN0.0260.000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3AFGAsiaAfghanistan2020-02-271.00.0NaNNaNNaNNaN0.0260.000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4AFGAsiaAfghanistan2020-02-281.00.0NaNNaNNaNNaN0.0260.000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5AFGAsiaAfghanistan2020-02-291.00.00.143NaNNaN0.00.0260.0000.004NaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6AFGAsiaAfghanistan2020-03-011.00.00.143NaNNaN0.00.0260.0000.004NaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7AFGAsiaAfghanistan2020-03-021.00.00.000NaNNaN0.00.0260.0000.000NaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8AFGAsiaAfghanistan2020-03-032.01.00.143NaNNaN0.00.0510.0260.004NaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9AFGAsiaAfghanistan2020-03-044.02.00.429NaNNaN0.00.1030.0510.011NaNNaN0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
iso_codecontinentlocationdatetotal_casesnew_casesnew_cases_smoothedtotal_deathsnew_deathsnew_deaths_smoothedtotal_cases_per_millionnew_cases_per_millionnew_cases_smoothed_per_milliontotal_deaths_per_millionnew_deaths_per_millionnew_deaths_smoothed_per_millionreproduction_rateicu_patientsicu_patients_per_millionhosp_patientshosp_patients_per_millionweekly_icu_admissionsweekly_icu_admissions_per_millionweekly_hosp_admissionsweekly_hosp_admissions_per_millionnew_teststotal_teststotal_tests_per_thousandnew_tests_per_thousandnew_tests_smoothed
9990BOLSouth AmericaBolivia2021-01-06166981.01713.01229.8579287.046.019.71414304.856146.749105.359795.5953.9411.6891.37NaNNaNNaNNaNNaNNaNNaNNaN3982.0431399.036.9570.3412989.0
9991BOLSouth AmericaBolivia2021-01-07168891.01910.01252.4299304.017.019.85714468.481163.625107.293797.0511.4561.7011.36NaNNaNNaNNaNNaNNaNNaNNaN4453.0435852.037.3380.3813016.0
9992BOLSouth AmericaBolivia2021-01-08171154.02263.01452.7149328.024.021.85714662.347193.866124.450799.1072.0561.8721.35NaNNaNNaNNaNNaNNaNNaNNaN5227.0441079.037.7860.4483491.0
9993BOLSouth AmericaBolivia2021-01-09172798.01644.01534.7149351.023.023.57114803.184140.837131.475801.0771.9702.0191.33NaNNaNNaNNaNNaNNaNNaNNaN3863.0444942.038.1170.3313671.0
9994BOLSouth AmericaBolivia2021-01-10173896.01098.01605.0009376.025.025.00014897.24794.063137.496803.2192.1422.1421.31NaNNaNNaNNaNNaNNaNNaNNaN2580.0447522.038.3380.2213822.0
9995BOLSouth AmericaBolivia2021-01-11175288.01392.01659.5719415.039.028.00015016.497119.249142.171806.5603.3412.3991.29NaNNaNNaNNaNNaNNaNNaNNaN3273.0450795.038.6190.2803924.0
9996BOLSouth AmericaBolivia2021-01-12176761.01473.01641.8579454.039.030.42915142.685126.188140.654809.9013.3412.6071.27NaNNaNNaNNaNNaNNaNNaNNaN3565.0454360.038.9240.3053849.0
9997BOLSouth AmericaBolivia2021-01-13178818.02057.01691.0009493.039.029.42915318.903176.218144.864813.2423.3412.5211.26NaNNaNNaNNaNNaNNaNNaNNaN5112.0459472.039.3620.4384010.0
9998BOLSouth AmericaBolivia2021-01-14181016.02198.01732.1439530.037.032.28615507.200188.297148.388816.4123.1702.7661.25NaNNaNNaNNaNNaNNaNNaNNaN5197.0464669.039.8070.4454117.0
9999BOLSouth AmericaBolivia2021-01-15183589.02573.01776.4299571.041.034.71415727.623220.423152.182819.9243.5122.9741.24NaNNaNNaNNaNNaNNaNNaNNaN6157.0470826.040.3350.5274250.0